The minimum standard deviations achievable for concurrent estimates of thresholds and psychometric function slopes as well as the optimal target values for adaptive procedures are calculated as functions of stimulus level and track length on the basis of the binomial theory. The optimum pair of targets for a concurrent estimate is found at the correct response probabilities p1 = 0.19 and p2 = 0.81 for the logistic psychometric function. An adaptive procedure that converges at these optimal targets is introduced and tested with Monte Carlo simulations. The efficiency increases rapidly when each subject's response consists of more than one statistically independent Bernoulli trial. Sentence intelligibility tests provide more than one Bernoulli trial per sentence when each word is scored separately. The number of within-sentence trials can be quantified by the j factor [Boothroyd and Nittrouer, J. Acoust. Soc. Am. 84, 101-114 (1988)]. The adaptive procedure was evaluated with 10 normal-hearing and 11 hearing-impaired listeners using two German sentence tests that differ in j factors. The expected advantage of the sentence test with the higher j factor was not observed, possibly due to training effects. Hence, the number of sentences required for a reliable speech reception threshold (approximately 1 dB standard deviation) concurrently with a slope estimate (approximately 20%-30% relative standard deviation) is at least N = 30 if word scoring for short, meaningful sentences (j approximately 2) is performed.

The matrix test format with the principles outlined here is recommended for producing efficient, reliable, and comparable speech reception thresholds across different languages.

Binaural speech intelligibility of individual listeners under realistic conditions was predicted using a model consisting of a gammatone filter bank, an independent equalization-cancellation (EC) process in each frequency band, a gammatone resynthesis, and the speech intelligibility index (SII). Hearing loss was simulated by adding uncorrelated masking noises (according to the pure-tone audiogram) to the ear channels. Speech intelligibility measurements were carried out with 8 normal-hearing and 15 hearing-impaired listeners, collecting speech reception threshold (SRT) data for three different room acoustic conditions (anechoic, office room, cafeteria hall) and eight directions of a single noise source (speech in front). Artificial EC processing errors derived from binaural masking level difference data using pure tones were incorporated into the model. Except for an adjustment of the SII-to-intelligibility mapping function, no model parameter was fitted to the SRT data of this study. The overall correlation coefficient between predicted and observed SRTs was 0.95. The dependence of the SRT of an individual listener on the noise direction and on room acoustics was predicted with a median correlation coefficient of 0.91. The effect of individual hearing impairment was predicted with a median correlation coefficient of 0.95. However, for mild hearing losses the release from masking was overestimated.

This study presents revision, extension, and evaluation of a binaural speech intelligibility model (Beutelmann, R., and Brand, T. (2006). J. Acoust. Soc. Am. 120, 331-342) that yields accurate predictions of speech reception thresholds (SRTs) in the presence of a stationary noise source at arbitrary azimuths and in different rooms. The modified model is based on an analytical expression of binaural unmasking for arbitrary input signals and is computationally more efficient, while maintaining the prediction quality of the original model. An extension for nonstationary interferers was realized by applying the model to short time frames of the input signals and averaging over the predicted SRT results. Binaural SRTs from 8 normal-hearing and 12 hearing-impaired subjects, incorporating all combinations of four rooms, three source setups, and three noise types were measured and compared to the model's predictions. Depending on the noise type, the parametric correlation coefficients between observed and predicted SRTs were 0.80-0.93 for normal-hearing subjects and 0.59-0.80 for hearing-impaired subjects. The mean absolute prediction error was 3 dB for the mean normal-hearing data and 4 dB for the individual hearing-impaired data. 70% of the variance of the SRTs of hearing-impaired subjects could be explained by the model, which is based only on the audiogram.